DATA ENGINEERING WITH DATABRICKS, PYSPARK & GENERATIVE AI COMBO

Featured Review

4.5 (2587 Ratings)

The Data Engineering with Databricks, PySpark & Generative AI Combo course is designed for learners who want to build practical skills in modern data engineering and AI-powered data workflows. The training covers Databricks, PySpark, data processing, ETL pipelines, data lakes, data transformation, and Generative AI applications through hands-on exercises and real-world projects. Learners gain experience working with large datasets and using AI tools to improve data workflows and productivity. This course is ideal for aspiring data engineers, software developers, data analysts, cloud professionals, freshers, and IT professionals looking to build skills in modern data engineering and Generative AI.

Duration of Training : 80 Hours
Batch type : Weekdays/Weekends
Mode of Training : Classroom/Online/Corporate Training
Detailed Syllabus • Hands-on Labs • Assignments • Support-Focused • Implementation

0 +

Google Reviews

0 +

JustDial Reviews

Overview

The Syllabus

Curriculum Designed by Experts

Program Overview

Become a Modern Data Engineer by mastering Python, SQL, Apache Spark, PySpark, Databricks, Delta Lake, Azure Data Factory, Apache Kafka, Data Warehousing, ETL/ELT, Cloud Data Engineering, Data Lakes, Generative AI, LLMs, AI Agents, RAG, Vector Databases, MLOps, and Production-Ready Data Pipelines.

This program is designed to prepare candidates for Data Engineering, Big Data Engineering, Analytics Engineering, AI Data Engineering, and Gen AI Data Engineer roles.

Who Should Join?

• Fresh Graduates
• Software Engineers
• Python Developers
• SQL Developers
• ETL Developers
• BI Developers
• Data Analysts
• Data Scientists
• Cloud Engineers
• DevOps Engineers
• Database Administrators
• AI/ML Enthusiasts
• Working Professionals looking to transition into Data Engineering

Prerequisites

• No prior Data Engineering experience required
• Basic computer knowledge
• Logical thinking
• Programming background is helpful but not mandatory

Course Highlights

• ✅Python Programming
• ✅Advanced SQL
• ✅Linux Fundamentals
• ✅Data Engineering Fundamentals
• ✅Apache Spark
• ✅PySpark
• ✅Databricks Lakehouse Platform
• ✅Delta Lake
• ✅Azure Data Factory
• ✅Apache Kafka
• ✅Azure Data Lake Storage (ADLS)
• ✅Data Warehousing
• ✅ETL & ELT Pipelines
• ✅Data Modeling
• ✅Git & GitHub
• ✅Azure DevOps / CI-CD
• ✅Docker Fundamentals
• ✅Generative AI
• ✅Large Language Models (LLMs)
• ✅Retrieval-Augmented Generation (RAG)
• ✅LangChain
• ✅LangGraph (Overview)
• ✅AI Agents
• ✅Vector Databases
• ✅Prompt Engineering
• ✅Production Projects

Module 1 – Data Engineering Fundamentals

• What is Data Engineering?
• Data Engineer Roles & Responsibilities
• Data Pipeline Architecture
• Batch vs Streaming
• Data Lakes
• Data Warehouses
• Lakehouse Architecture
• Medallion Architecture
• Enterprise Data Platforms Data Warehouses
• Lakehouse Architecture
• Medallion Architecture
• Enterprise Data Platforms

Module 2 – Python for Data Engineering

• Python Basics
• OOP Concepts
• File Handling
• Exception Handling
• Functions
• Modules
• Pandas
• NumPy
• API Calls
• JSON Processing
• Logging
• Virtual Environments

Module 3 – SQL from Basic to Advanced

• SELECT
• JOIN
• GROUP BY
• Window Functions
• CTE (Common Table Expressions)
• Stored Procedures
• Indexing
• Performance Tuning
• Query Optimization
• Advanced SQL Interview Questions

Module 4 – Linux for Data Engineers

• Linux Commands
• Shell Scripting
• File Management
• Permissions
• Cron Jobs
• Process Management

Module 5 – Apache Spark

• Spark Architecture
• Spark Cluster
• Spark SQL
• RDD
• DataFrames
• Transformations
• Actions
• Caching
• Partitioning
• Optimization

Module 6 – PySpark

• DataFrame API
• Spark SQL
• Data Cleaning
• Data Transformation
• Aggregations
• Window Functions
• UDFs
• Performance Optimization
• Partitioning
• Broadcast Joins

Module 7 – Databricks

• Databricks Workspace
• Clusters
• Notebooks
• Jobs
• Workflows
• Unity Catalog
• Databricks SQL
• Secrets
• Widgets
• Repos
• Asset Bundles (Overview)

Module 8 – Delta Lake

• ACID Transactions
• Delta Tables
• Time Travel
• Schema Evolution
• Merge Operations
• Upserts
• Change Data Feed (CDF)
• Delta Optimization
• Vacuum
• Z-Ordering

Module 9 – Azure Data Factory (ADF)

• Linked Services
• Pipelines
• Data Flows
• Integration Runtime
• Triggers
• Parameterization
• Scheduling
• Monitoring

Module 10 – Azure Data Lake Storage (ADLS)

• Storage Accounts
• Containers
• File Management
• Security
• Data Organization

Module 11 – Apache Kafk

• Kafka Architecture
• Producers
• Consumers
• Topics
• Partitions
• Streaming Pipelines
• Real-Time Processing

Module 12 – Data Warehousing

• Star Schema
• Snowflake Schema
• Slowly Changing Dimensions (SCD)
• Fact Tables
• Dimension Tables
• Data Modeling

Module 13 – ETL & ELT

• ETL Design
• ELT Pipelines
• Incremental Loads
• CDC Concepts
• Workflow Automation
• Error Handling
• Logging

Module 14 – Cloud Data Engineering

• Azure Data Platform
• Databricks on Azure
• Storage Integration
• Identity & Access Management
• Cost Optimization

Module 15 – Generative AI for Data Engineers

• Introduction to Generative AI
• Large Language Models (LLMs)
• Foundation Models
• Prompt Engineering
• AI APIs
• OpenAI API Concepts
• Azure OpenAI Concepts
• Model Selection

Module 16 – Retrieval-Augmented Generation (RAG)

• Embeddings
• Vector Databases
• Similarity Search
• Chunking Strategies
• Retrieval Pipelines
• Hybrid Search

Module 17 – LangChain & AI Agents

• LangChain Fundamentals
• Chains
• Agents
• Memory
• Tool Calling
• Multi-Step Workflows
• LangGraph Overview
• MCP (Model Context Protocol) Concepts

Module 18 – Production Data Engineering

• CI/CD
• GitHub
• Azure DevOps
• Monitoring
• Logging
• Testing
• Data Quality
• Deployment
• Security
• Governance

Hands-on Labs

Students will build practical solutions including:

• Python ETL Scripts
• SQL Optimization Labs
• Spark Transformations
• PySpark Data Pipelines
• Databricks Notebook Development
• Delta Lake Implementation
• Azure Data Factory Pipelines
• Kafka Streaming Pipelines
• Data Warehouse Design
• Data Lake Implementation
• REST API Data Ingestion
• Incremental Loading
• RAG Pipeline
• AI Chatbot using Enterprise Data
• Vector Search Integration
• End-to-End Lakehouse Pipeline

Assignments

• Python Coding Assignments
• SQL Challenges
• Spark Transformations
• Databricks Notebook Exercises
• Delta Lake Labs
• Kafka Streaming Exercises
• ADF Pipeline Development
• ETL Design
• Data Modeling
• Prompt Engineering Tasks
• RAG Implementation Exercises

Mini Projects

Project 1
Retail Sales ETL Pipeline

Project 2
Customer Analytics Platform

Project 3
Real-Time Streaming with Kafka & PySpark

Project 4
Data Lakehouse on Databricks

Project 5
Healthcare Data Engineering Pipeline

Project 6
AI-Powered Enterprise Knowledge Assistant

Capstone Project

Enterprise Data Lakehouse with Generative AI
The final project includes:
• Multi-source Data Ingestion
• Azure Data Lake Storage
• Databricks Processing
• Delta Lake Architecture
• Medallion Architecture (Bronze, Silver, Gold)
• Apache Kafka Streaming
• Azure Data Factory Orchestration
• Enterprise Data Warehouse
• Dashboard Data Layer
• RAG Implementation
• Enterprise AI Chatbot
• Vector Database Integration
• Production Deployment
• Monitoring & Logging

Real-Time Job-Oriented Scenarios

• Batch ETL Failures
• Streaming Pipeline Issues
• Data Quality Problems
• Schema Evolution
• Delta Merge Conflicts
• Late Arriving Data
• Slowly Changing Dimensions
• CDC Implementation
• Pipeline Performance Optimization
• Cloud Cost Optimization
• AI Integration into Data Pipelines
• Enterprise Data Governance

Troubleshooting Scenarios

• Spark Job Failures
• Databricks Cluster Issues
• Memory Optimization
• Shuffle Problems
• Kafka Consumer Lag
• ADF Pipeline Errors
• Delta Table Corruption Recovery
• Permission Issues
• Performance Bottlenecks
• AI API Failures
• Vector Search Issues

Industry Tools Covered

Programming
• Python
• SQL
• Linux

Big Data
• Apache Spark
• PySpark
• Delta Lake
• Apache Kafka

Cloud
• Microsoft Azure
• Azure Data Factory
• Azure Data Lake Storage
• Azure Key Vault (Overview)

Data Platform
• Databricks
• Unity Catalog
• Databricks SQL

AI & GenAI
• OpenAI API Concepts
• Azure OpenAI Concepts
• LangChain
• LangGraph
• Vector Databases (FAISS, ChromaDB, Pinecone concepts)
• Ollama (Local LLM Overview)

DevOps
• Git
• GitHub
• Azure DevOps
• Docker
• CI/CD Concepts

Best Practices

• Lakehouse Architecture
• Medallion Design Pattern
• Data Quality Frameworks
• Secure Credential Management
• Performance Optimization
• Cost Optimization
• Incremental Processing
• Data Governance
• Naming Standards
• CI/CD for Data Pipelines
• AI Governance & Responsible AI
• Documentation Standards

Recommended Certifications

• Databricks Certified Data Engineer Associate
• Databricks Certified Data Engineer Professional
• Microsoft Certified: Azure Data Engineer Associate (DP-203)
• Microsoft Certified: Azure Fundamentals (AZ-900)
• Microsoft Certified: Azure AI Fundamentals (AI-900)
• Apache Spark Certification (where available)
• Snowflake SnowPro Core (optional for broader career opportunities)

Mock Interview Preparation

Our interview preparation includes:

• Python and SQL coding assessments.
• Spark and PySpark technical interviews.
• Databricks architecture discussions.
• Data modeling and ETL design questions.
• Cloud and Azure data engineering scenarios.
• GenAI, RAG, and LLM implementation discussions.
• Production support scenarios.
• HR interview preparation.
• Project presentations with expert feedback.
• Final enterprise-style mock interviews.

Resume Preparation

We help candidates with:

1. ATS-friendly resume creation.
2. Highlighting end-to-end Data Engineering projects.
3. Optimizing resumes with Databricks, Spark, Azure, and GenAI keywords.
4. Writing impactful project descriptions.
5. LinkedIn profile optimization.
6. GitHub portfolio guidance.
7. Professional summary creation.
8. Resume review sessions.
9. Role-specific resume customization.
10. Final interview-ready resume validation.

Placement Assistance

We provide comprehensive placement support through:

• Resume forwarding to 850+ Hiring Partners
• Dedicated placement team
• Technical interview scheduling
• Mock interviews
• HR interview coaching
• Career mentoring
• LinkedIn branding
• Job alerts
• Salary negotiation guidance
• Continuous support until placement

Latest Industry Topics

• Lakehouse Architecture
• Data Mesh
• Data Fabric
• Delta Live Tables
• Databricks Unity Catalog
• AI-Powered Data Engineering
• Generative AI for Data Pipelines
• Agentic AI
• Retrieval-Augmented Generation (RAG)
• AI Agents for Analytics
• Real-Time Analytics
• Data Observability
• Microsoft Fabric (Overview)
• Apache Iceberg & Open Table Formats (Overview)

How This Course Benefits Different Experience Levels

Freshers
• Build a strong foundation in Data Engineering.
• Learn job-ready technologies through projects and hands-on labs.
• Become eligible for Junior Data Engineer roles.

1–3 Years of Experience
• Upskill to modern cloud and big data technologies.
• Transition from SQL/ETL/BI roles into Data Engineering.
• Gain practical exposure to Databricks and PySpark.

3–7 Years of Experience
• Advance into Senior Data Engineer or Lead Data Engineer roles.
• Learn scalable architectures, optimization, and AI integration.

7+ Years of Experience
• Prepare for Data Architect, Cloud Data Architect, AI Data Engineer, or Engineering Manager roles.
• Build expertise in enterprise data platforms, governance, and GenAI adoption.

Current Market Scenario

Organizations are rapidly modernizing their analytics platforms using cloud-native lakehouses and real-time data pipelines. Databricks, Apache Spark, and PySpark have become core technologies for processing large-scale data, while Generative AI is creating new opportunities to build intelligent data products, AI-powered search, and enterprise knowledge assistants. Employers increasingly seek professionals who combine strong data engineering fundamentals with cloud, automation, and AI capabilities.

Future Outlook (Next 10 Years)

Over the next decade, Data Engineering is expected to remain one of the most in-demand technology domains. Growth in AI, real-time analytics, IoT, and cloud computing will continue driving demand for scalable data platforms. Professionals skilled in Databricks, PySpark, cloud data engineering, and Generative AI are expected to play a central role in building enterprise AI systems, modern data platforms, and intelligent business applications. This combination of Data Engineering and GenAI positions candidates for long-term, highgrowth career opportunities across industries.

Enquire Now

Why Radical Technologies

Live Online Training

Highly practical oriented training

Installation of Software On your System

24/7 Email and Phone Support

100% Placement Assistance until you get placed

Global Certification Preparation

Trainer Student Interactive Portal

Assignments and Projects Guided by Mentors

And Many More Features

Course completion certificate and Global Certifications are part of our all Master Program

Live Classroom Training

Weekend / Weekdays / Morning / Evening Batches

80:20 Practical and Theory Ratio

Real-life Case Studies

Easy Coverup if you missed any sessions

PSI | Kryterion | Redhat Test Centers

Life Time Video Classroom Access ( coming soon )

Resume Preparations and Mock Interviews

And Many More Features

Course completion certificate and Global Certifications are part of our all Master Program

Self Paced Training

Self Paced Learning

Learn 300+ Courses at Your Own Time

50000+ Satisfied Learners

Course Completion Certificate

Practical Labs Available

Mentor Support Available

Doubt Clearing Session Available

Attend Our Virtual Job Fair

10% Discounted Global Certification

Course completion certificate and Global Certifications are part of our all Master Program

Like the Curriculum ? Let's Get Started

Global Certification

Radical Technologies is the leading IT certification institute in Kochi, offering a wide range of globally recognized certifications across various domains. With expert trainers and comprehensive course materials, it ensures that students gain in-depth knowledge and hands-on experience to excel in their careers. The institute’s certification programs are tailored to meet industry standards, helping professionals enhance their skillsets and boost their career prospects. From cloud technologies to data science, Radical Technologies covers it all, empowering individuals to stay ahead in the ever-evolving tech landscape. Achieve your professional goals with certifications that matter.

Discount Voucher

"Register Now to Secure Your Spot in Our Featured Course !"

BOOK HERE

career services

Job Assistance
Interview Preparation
Profile Buliding

At Radical Technologies, we are committed to your success beyond the classroom. Our 100% Job Assistance program ensures that you are not only equipped with industry-relevant skills but also guided through the job placement process. With personalized resume building, interview preparation, and access to our extensive network of hiring partners, we help you take the next step confidently into your IT career. Join us and let your journey to a successful future begin with the right support.

At Radical Technologies, we ensure you’re ready to shine in any interview. Our comprehensive Interview Preparation program includes mock interviews, expert feedback, and tailored coaching sessions to build your confidence. Learn how to effectively communicate your skills, handle technical questions, and make a lasting impression on potential employers. With our guidance, you’ll walk into your interviews prepared and poised for success.

At Radical Technologies, we believe that a strong professional profile is key to standing out in the competitive IT industry. Our Profile Building services are designed to highlight your unique skills and experiences, crafting a resume and LinkedIn profile that resonate with employers. From tailored advice on showcasing your strengths to tips on optimizing your online presence, we provide the tools you need to make a lasting impression. Let us help you build a profile that opens doors to your dream career.

Radical Learning Eco-System

Exam simulator

Cloud SandBox

Hands - on Cloud Lab

Developer Coding Ground

Testimonials

Play

Our Alumni

Online Batches Available for the Areas

Data Engineering With Databricks, Pyspark & Generative AI Combo Course Certification with Training In Kochi

Q: Program Overview

Become a Modern Data Engineer by mastering Python, SQL, Apache Spark, PySpark, Databricks, Delta Lake, Azure Data Factory, Apache Kafka, Data Warehousing, ETL/ELT, Cloud Data Engineering, Data Lakes, Generative AI, LLMs, AI Agents, RAG, Vector Databases, MLOps, and Production-Ready Data Pipelines. This program is designed to prepare candidates for Data Engineering, Big Data Engineering, Analytics Engineering, AI Data Engineering, and Gen AI Data Engineer roles.

At Radical Technologies, we are committed to providing world-class Azure Data Engineer Training in Bangalore, helping aspiring data professionals master the skills needed to excel in the rapidly growing field of cloud data engineering. As the leading institute for Azure Data Engineer Course In Bangalore, we offer comprehensive, hands-on training designed to meet the demands of today’s data-driven organizations.

Our Azure Data Engineer Training Bangalore program covers every aspect of the Azure Data Engineer Syllabus, ensuring that students receive in-depth knowledge of data architecture, data processing, and data storage on Microsoft Azure. Whether you prefer attending classes in-person or via Azure Data Engineer Online Training, Radical Technologies provides flexible learning options to suit your needs.

Our Azure Data Engineering Training is renowned for its practical, real-world approach. Students have access to an industry-leading Azure Data Engineer Bootcamp, which combines theory and hands-on labs to ensure they are fully prepared for their certification exams. The Microsoft Azure Data Engineer Training is tailored to cover all key topics, from data integration to security, and is led by experienced professionals who are experts in their field.

For professionals and organizations seeking Azure Data Engineering Corporate Training, we offer tailored courses that address specific business needs. Our Azure Data Engineering Corporate Training Course ensures that teams gain practical experience in building scalable, secure, and efficient data solutions on Azure.

At Radical Technologies, our Azure Data Engineer Courses are structured to ensure that both beginners and experienced professionals alike can enhance their knowledge. The Azure Data Engineer Certification Training offered here equips students with the skills and credentials needed to stand out in a competitive job market.

Our institute also offers the Azure Data Engineer Full Course, which provides a comprehensive pathway for mastering Azure Data Engineering concepts and techniques. We take pride in being one of the top Azure Data Engineer Institutes in Bangalore, with a proven track record of helping students achieve their Azure Data Engineering Certification.

Whether you are looking for Azure Data Engineer Training Online or prefer our in-person classes in Bangalore, Radical Technologies is your trusted partner for career advancement in data engineering. Join us today to enroll in the Best Azure Data Engineer Course and kick-start your journey towards becoming a certified data engineer.